This analysis document compliments FIA NLS Models: Biomass Growth vs. Stand Age. All of the background information from that document applies to these analyses, which are extensions to them. The difference between that document and this analysis is the use of different data subsets.
Here, we fit the models using: 1) a temporally-balanced dataset, where we take the first and most-recent plot record for all plots in the dataset, 2) a temporally-balanced dataset (same as #1), but which excludes plot locations which have experienced harvest (at any point over the study interval 2000-2022)
Below the model fitting procedure is implemented by ecoprovince:
Lets look at some quick attributes of the dataset
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4810 1461.8
## 2 4809 1399.7 1 62.047 213.17 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 18812.07
## 2 2 18605.23
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.2407 0.1786 1.348 0.17773
## alpha 0.6366 0.0409 15.566 < 2e-16 ***
## a 0.0000 1.6712 0.000 1.00000
## b 3.4218 1.6636 2.057 0.03975 *
## c 35.4219 2.1472 16.497 < 2e-16 ***
## d 2.5909 0.7967 3.252 0.00115 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5395 on 4809 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (23 observations deleted due to missingness)
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## Warning: Removed 11 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 9800 4156.3
## 2 9799 3887.7 1 268.62 677.07 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 35940.91
## 2 2 35287.81
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.28350 0.21473 5.977 2.35e-09 ***
## alpha 0.79675 0.02806 28.392 < 2e-16 ***
## a 0.33195 0.27692 1.199 0.231
## b 2.04010 0.28037 7.276 3.69e-13 ***
## c 24.65429 0.85760 28.748 < 2e-16 ***
## d 2.38823 0.25052 9.533 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6299 on 9799 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3157 observations deleted due to missingness)
## Warning: Removed 1573 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5409 2038.5
## 2 5408 1963.5 1 74.951 206.44 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 23802.80
## 2 2 23601.98
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.36151 0.16281 -2.220 0.02643 *
## alpha 0.70293 0.04605 15.265 < 2e-16 ***
## a 0.00000 2.13615 0.000 1.00000
## b 4.31575 2.13643 2.020 0.04342 *
## c 38.22036 2.84147 13.451 < 2e-16 ***
## d 2.71967 0.87701 3.101 0.00194 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6026 on 5408 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (32 observations deleted due to missingness)
## Warning: Removed 19 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2728 971.74
## 2 2727 905.51 1 66.232 199.46 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 10962.43
## 2 2 10771.51
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.19328 0.27462 0.704 0.48162
## alpha 0.82686 0.05321 15.541 < 2e-16 ***
## a 1.32113 0.48479 2.725 0.00647 **
## b 2.04132 0.48660 4.195 2.81e-05 ***
## c 48.17441 4.15142 11.604 < 2e-16 ***
## d 1.97547 0.41678 4.740 2.25e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5762 on 2727 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (819 observations deleted due to missingness)
## Warning: Removed 425 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5252 2143.2
## 2 5251 2096.6 1 46.648 116.83 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 21906.12
## 2 2 21792.43
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.51043 0.14538 -3.511 0.00045 ***
## alpha 0.57800 0.05061 11.421 < 2e-16 ***
## a 2.44659 0.37027 6.608 4.29e-11 ***
## b 1.56434 0.36338 4.305 1.70e-05 ***
## c 31.40267 2.53357 12.395 < 2e-16 ***
## d 1.27701 0.27810 4.592 4.49e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6319 on 5251 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1131 observations deleted due to missingness)
## Warning: Removed 582 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7673 3589.5
## 2 7672 3215.8 1 373.72 891.59 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 38236.36
## 2 2 37394.22
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.52751 0.20834 7.332 2.5e-13 ***
## alpha 0.88547 0.02685 32.984 < 2e-16 ***
## a 1.07937 0.36028 2.996 0.00274 **
## b 3.52854 0.36094 9.776 < 2e-16 ***
## c 18.62841 0.50436 36.935 < 2e-16 ***
## d 1.90401 0.16277 11.697 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6474 on 7672 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (112 observations deleted due to missingness)
## Warning: Removed 60 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7807 5112.9
## 2 7806 4675.8 1 437.1 729.71 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 39574.71
## 2 2 38878.58
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.68024 0.26003 6.462 1.1e-10 ***
## alpha 0.86337 0.02851 30.287 < 2e-16 ***
## a 2.12476 0.16290 13.044 < 2e-16 ***
## b 2.07094 0.15293 13.541 < 2e-16 ***
## c 17.38074 0.65206 26.655 < 2e-16 ***
## d 1.25393 0.10522 11.918 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.774 on 7806 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (128 observations deleted due to missingness)
## Warning: Removed 63 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 802 465.89
## 2 801 437.60 1 28.288 51.778 1.43e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4064.862
## 2 2 4016.313
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.68067 0.73953 0.920 0.357638
## alpha 0.79965 0.09996 7.999 4.37e-15 ***
## a 3.02218 0.63011 4.796 1.93e-06 ***
## b 2.13229 0.57374 3.716 0.000216 ***
## c 21.44192 3.43187 6.248 6.75e-10 ***
## d 0.91822 0.33809 2.716 0.006752 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7391 on 801 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (23 observations deleted due to missingness)
## Warning: Removed 8 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 976 333.50
## 2 975 329.85 1 3.6469 10.78 0.001063 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3706.157
## 2 2 3697.370
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.2660 0.4874 0.546 0.585312
## alpha 0.4179 0.1217 3.435 0.000617 ***
## a 0.0000 5.3686 0.000 1.000000
## b 2.8573 5.3800 0.531 0.595476
## c 26.7202 9.6781 2.761 0.005873 **
## d 3.5196 4.4523 0.791 0.429422
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5816 on 975 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (411 observations deleted due to missingness)
## Warning: Removed 224 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_segment()`).
## Warning: Removed 1 rows containing missing values (`geom_segment()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 420 832.94
## 2 419 825.85 1 7.0966 3.6005 0.05845 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 2318.893
## 2 2 2317.256
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.1889 2.0929 0.568 0.57030
## alpha 0.6203 0.3008 2.062 0.03984 *
## a 0.0000 1.1030 0.000 1.00000
## b 3.5531 1.6428 2.163 0.03112 *
## c 18.6079 2.9988 6.205 1.31e-09 ***
## d 1.3099 0.4895 2.676 0.00774 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.404 on 419 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (19 observations deleted due to missingness)
## Warning: Removed 10 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5090 1413.3
## 2 5089 1338.2 1 75.173 285.88 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 19343.53
## 2 2 19067.06
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.09007 0.24656 4.421 1e-05 ***
## alpha 0.63616 0.03509 18.127 <2e-16 ***
## a 0.97615 1.26167 0.774 0.4391
## b 1.95500 1.24894 1.565 0.1176
## c 34.19072 2.32877 14.682 <2e-16 ***
## d 2.20422 0.90326 2.440 0.0147 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5128 on 5089 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (13 observations deleted due to missingness)
## Warning: Removed 7 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5154 2644.7
## 2 5153 2580.9 1 63.714 127.21 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 24436.20
## 2 2 24312.39
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.88368 0.25792 3.426 0.000617 ***
## alpha 0.81056 0.06798 11.923 < 2e-16 ***
## a 1.86507 0.58588 3.183 0.001464 **
## b 2.08079 0.55574 3.744 0.000183 ***
## c 27.63128 2.24333 12.317 < 2e-16 ***
## d 1.51203 0.36801 4.109 4.04e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7077 on 5153 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (27 observations deleted due to missingness)
## Warning: Removed 14 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 594 360.14
## 2 593 349.15 1 10.99 18.666 1.826e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 2541.955
## 2 2 2525.391
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 3.2969 1.7985 1.833 0.067280 .
## alpha 0.9650 0.2059 4.686 3.45e-06 ***
## a 1.4792 0.3538 4.181 3.34e-05 ***
## b 1.2132 0.4566 2.657 0.008094 **
## c 30.4913 2.7871 10.940 < 2e-16 ***
## d 0.4209 0.1126 3.736 0.000205 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7673 on 593 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3 observations deleted due to missingness)
## Warning: Removed 1 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 672 368.32
## 2 671 349.67 1 18.647 35.783 3.587e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 2860.020
## 2 2 2826.847
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 5.0000 2.7919 1.791 0.073756 .
## alpha 0.9432 0.1463 6.445 2.21e-10 ***
## a 1.3379 0.3993 3.351 0.000852 ***
## b 0.7534 0.8698 0.866 0.386754
## c 5.7656 10.3109 0.559 0.576226
## d 1.1578 1.2049 0.961 0.336943
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7219 on 671 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3 observations deleted due to missingness)
## Warning: Removed 3 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 210 220.84
## 2 209 208.75 1 12.085 12.099 0.0006136 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 714.2646
## 2 2 704.1649
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.1264 1.6830 -0.075 0.940186
## alpha 0.8046 0.2067 3.893 0.000133 ***
## a 0.0000 14.2323 0.000 1.000000
## b 1.4399 14.2300 0.101 0.919497
## c 71.0209 27.5153 2.581 0.010532 *
## d 1.8423 11.1488 0.165 0.868910
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9994 on 209 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (91 observations deleted due to missingness)
## Warning: Removed 47 rows containing missing values (`geom_point()`).
## Warning: Removed 2 rows containing missing values (`geom_point()`).
## Warning: Removed 2 rows containing missing values (`geom_pointrange()`).
## Warning: Removed 2 rows containing missing values (`geom_point()`).
## Warning: Removed 2 rows containing missing values (`geom_pointrange()`).
## [1] "cannot plot data with prediction"
| Code | Ecoregion | Sel.Mod |
|---|---|---|
| 211 | Northeastern Mixed Forest | 2 |
| 212 | Laurentian Mixed Forest | 2 |
| 221 | Eastern Broadleaf Forest | 2 |
| 222 | Midwest Broadleaf Forest | 2 |
| 223 | Central Interior Broadleaf Forest | 2 |
| 231 | Southeastern Mixed Forest | 2 |
| 232 | Outer Coastal Plain Mixed Forest | 2 |
| 234 | Lower Mississippi Riverine Forest | 2 |
| 242 | Pacific Lowland Mixed Forest | NA |
| 251 | Prairie Parkland (Temperate) | 2 |
| 255 | Prairie Parkland (Subtropical) | 2 |
| 261 | California Coastal Chaparral Forest and Shrub | NA |
| 262 | California Dry Steppe | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA |
| 313 | Colorado Plateau Semi-Desert | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA |
| 321 | Chihuahuan Semi-Desert | NA |
| 322 | American Semidesert and Desert | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA |
| 332 | Great Plains Steppe | NA |
| 341 | Intermountain Semi-Desert and Desert | NA |
| 342 | Intermountain Semi-Desert | NA |
| 411 | Everglades | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 2 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 2 |
| M223 | Ozark Broadleaf Forest Meadow | 2 |
| M231 | Ouachita Mixed Forest | 2 |
| M242 | Cascade Mixed Forest | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | NA |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA |
| M334 | Black Hills Coniferous Forest | 2 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA |
| Code | Ecoregion | region | n.obs | n.plots | tau | tau.variance | tau.2.5 | tau.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | a | a.2.5 | a.97.5 | b | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 4838 | 2419 | 0.2407307 | 0.0318940 | -0.1093852 | 0.5908466 | 0.6366052 | 0.0016727 | 0.5564260 | 0.7167845 | 0.0000000 | -3.2764180 | 3.2764180 | 3.4218034 | 0.1603849 | 6.683222 | 35.421923 | 31.212391 | 39.63145 | 2.5909373 | 1.0289425 | 4.1529320 |
| 212 | Laurentian Mixed Forest | east | 12962 | 6481 | 1.2834957 | 0.0461109 | 0.8625717 | 1.7044197 | 0.7967510 | 0.0007875 | 0.7417423 | 0.8517598 | 0.3319524 | -0.2108728 | 0.8747776 | 2.0401034 | 1.4905122 | 2.589694 | 24.654288 | 22.973222 | 26.33536 | 2.3882279 | 1.8971604 | 2.8792954 |
| 221 | Eastern Broadleaf Forest | east | 5446 | 2723 | -0.3615051 | 0.0265069 | -0.6806771 | -0.0423331 | 0.7029289 | 0.0021203 | 0.6126581 | 0.7931997 | 0.0000000 | -4.1877168 | 4.1877168 | 4.3157517 | 0.1274891 | 8.504014 | 38.220365 | 32.649930 | 43.79080 | 2.7196661 | 1.0003695 | 4.4389626 |
| 222 | Midwest Broadleaf Forest | east | 3552 | 1776 | 0.1932761 | 0.0754170 | -0.3452113 | 0.7317634 | 0.8268602 | 0.0028308 | 0.7225328 | 0.9311876 | 1.3211293 | 0.3705391 | 2.2717194 | 2.0413216 | 1.0871790 | 2.995464 | 48.174412 | 40.034159 | 56.31466 | 1.9754729 | 1.1582391 | 2.7927066 |
| 223 | Central Interior Broadleaf Forest | east | 6388 | 3194 | -0.5104308 | 0.0211344 | -0.7954297 | -0.2254320 | 0.5780045 | 0.0025614 | 0.4787870 | 0.6772220 | 2.4465926 | 1.7207101 | 3.1724750 | 1.5643357 | 0.8519575 | 2.276714 | 31.402667 | 26.435818 | 36.36952 | 1.2770141 | 0.7318236 | 1.8222047 |
| 231 | Southeastern Mixed Forest | east | 7790 | 3895 | 1.5275075 | 0.0434045 | 1.1191091 | 1.9359059 | 0.8854662 | 0.0007207 | 0.8328416 | 0.9380908 | 1.0793663 | 0.3731250 | 1.7856076 | 3.5285383 | 2.8210030 | 4.236073 | 18.628410 | 17.639721 | 19.61710 | 1.9040140 | 1.5849329 | 2.2230951 |
| 232 | Outer Coastal Plain Mixed Forest | east | 7940 | 3970 | 1.6802446 | 0.0676175 | 1.1705090 | 2.1899802 | 0.8633743 | 0.0008126 | 0.8074945 | 0.9192540 | 2.1247568 | 1.8054350 | 2.4440785 | 2.0709394 | 1.7711461 | 2.370733 | 17.380742 | 16.102525 | 18.65896 | 1.2539274 | 1.0476777 | 1.4601771 |
| 234 | Lower Mississippi Riverine Forest | east | 830 | 415 | 0.6806672 | 0.5469034 | -0.7709769 | 2.1323112 | 0.7996511 | 0.0099926 | 0.6034306 | 0.9958717 | 3.0221780 | 1.7853184 | 4.2590376 | 2.1322889 | 1.0060814 | 3.258496 | 21.441924 | 14.705397 | 28.17845 | 0.9182159 | 0.2545666 | 1.5818652 |
| 242 | Pacific Lowland Mixed Forest | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 1392 | 696 | 0.2660455 | 0.2375785 | -0.6904679 | 1.2225590 | 0.4179242 | 0.0148020 | 0.1791720 | 0.6566764 | 0.0000000 | -10.5352527 | 10.5352527 | 2.8572644 | -7.7004058 | 13.414935 | 26.720218 | 7.727881 | 45.71255 | 3.5195623 | -5.2175709 | 12.2566956 |
| 255 | Prairie Parkland (Subtropical) | east | 444 | 222 | 1.1888589 | 4.3801029 | -2.9249730 | 5.3026908 | 0.6203062 | 0.0905101 | 0.0289451 | 1.2116674 | 0.0000000 | -2.1681198 | 2.1681198 | 3.5531088 | 0.3239081 | 6.782310 | 18.607909 | 12.713432 | 24.50239 | 1.3099428 | 0.3477800 | 2.2721056 |
| 261 | California Coastal Chaparral Forest and Shrub | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | west | 118 | 59 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | west | 154 | 77 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 341 | Intermountain Semi-Desert and Desert | west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | west | 2 | 1 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 66 | 33 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 5108 | 2554 | 1.0900669 | 0.0607930 | 0.6066987 | 1.5734351 | 0.6361575 | 0.0012316 | 0.5673578 | 0.7049571 | 0.9761451 | -1.4972711 | 3.4495613 | 1.9550016 | -0.4934585 | 4.403462 | 34.190718 | 29.625330 | 38.75611 | 2.2042212 | 0.4334392 | 3.9750031 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 5186 | 2593 | 0.8836790 | 0.0665226 | 0.3780468 | 1.3893112 | 0.8105585 | 0.0046215 | 0.6772863 | 0.9438308 | 1.8650716 | 0.7165000 | 3.0136432 | 2.0807897 | 0.9913069 | 3.170273 | 27.631280 | 23.233399 | 32.02916 | 1.5120304 | 0.7905689 | 2.2334920 |
| M223 | Ozark Broadleaf Forest Meadow | east | 602 | 301 | 3.2968837 | 3.2344864 | -0.2352575 | 6.8290250 | 0.9649685 | 0.0424011 | 0.5605566 | 1.3693804 | 1.4791696 | 0.7843063 | 2.1740329 | 1.2131708 | 0.3164662 | 2.109875 | 30.491278 | 25.017567 | 35.96499 | 0.4208667 | 0.1996297 | 0.6421037 |
| M231 | Ouachita Mixed Forest | east | 680 | 340 | 5.0000000 | 7.7944526 | -0.4818226 | 10.4818226 | NA | NA | NA | NA | 1.3378653 | 0.5538449 | 2.1218857 | 0.7533553 | -0.9545851 | 2.461296 | 5.765626 | -14.479809 | 26.01106 | 1.1577725 | -1.2079946 | 3.5235396 |
| M242 | Cascade Mixed Forest | west | 34 | 17 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | west | 330 | 165 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | west | 8 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | west | 20 | 10 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | west | 22 | 11 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | west | 306 | 153 | -0.1264331 | 2.8323248 | -3.4441686 | 3.1913023 | 0.8046391 | 0.0427282 | 0.3971392 | 1.2121389 | 0.0000000 | -28.0572665 | 28.0572665 | 1.4399205 | -26.6127698 | 29.492611 | 71.020853 | 16.777839 | 125.26387 | 1.8422905 | -20.1361523 | 23.8207333 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I
## Warning: package 'ggnewscale' was built under R version 4.2.1
## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation ideoms with `aes()`
## Warning: The `size` argument of `element_line()` is deprecated as of ggplot2 3.4.0.
## ℹ Please use the `linewidth` argument instead.
## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
## found in Windows font database
## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
## found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning: Removed 21 rows containing missing values (`geom_point()`).
## Warning: Removed 21 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_hline()`).
## Warning: Removed 22 rows containing missing values (`geom_point()`).
## Warning: Removed 21 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4729 1518.4
## 2 4728 1497.6 1 20.77 65.572 7.066e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 18976.29
## 2 2 18913.09
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.55154 0.24459 2.255 0.02418 *
## alpha 0.69380 0.08191 8.471 < 2e-16 ***
## a 0.00000 1.89752 0.000 1.00000
## b 3.29975 1.88697 1.749 0.08041 .
## c 32.96538 1.92687 17.108 < 2e-16 ***
## d 2.48730 0.88804 2.801 0.00512 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5628 on 4728 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (38 observations deleted due to missingness)
## Warning: Removed 18 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 14324 6454.5
## 2 14323 6353.0 1 101.41 228.63 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 52899.90
## 2 2 52674.98
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.1876 0.1970 6.028 1.7e-09 ***
## alpha 0.6832 0.0429 15.926 < 2e-16 ***
## a 0.5003 0.1918 2.609 0.0091 **
## b 1.8381 0.1949 9.433 < 2e-16 ***
## c 25.3009 0.7774 32.546 < 2e-16 ***
## d 2.0440 0.1709 11.960 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.666 on 14323 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (2821 observations deleted due to missingness)
## Warning: Removed 1382 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5737 2245.5
## 2 5736 2212.0 1 33.502 86.877 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 25703.92
## 2 2 25619.61
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.49211 0.16644 -2.957 0.003123 **
## alpha 0.70784 0.07268 9.740 < 2e-16 ***
## a 0.00000 1.72362 0.000 1.000000
## b 4.43677 1.72532 2.572 0.010149 *
## c 39.60558 2.44144 16.222 < 2e-16 ***
## d 2.56369 0.66008 3.884 0.000104 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.621 on 5736 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (60 observations deleted due to missingness)
## Warning: Removed 25 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3581 1455.3
## 2 3580 1418.9 1 36.397 91.835 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 14852.55
## 2 2 14763.72
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.02831 0.26269 0.108 0.914
## alpha 0.71160 0.06935 10.262 < 2e-16 ***
## a 1.46035 0.28196 5.179 2.35e-07 ***
## b 1.91589 0.28501 6.722 2.08e-11 ***
## c 49.13281 3.10887 15.804 < 2e-16 ***
## d 1.64185 0.25033 6.559 6.21e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6295 on 3580 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (778 observations deleted due to missingness)
## Warning: Removed 399 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6509 2848.8
## 2 6508 2833.4 1 15.37 35.303 2.968e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 27147.39
## 2 2 27114.15
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.08251 0.18363 -0.449 0.653
## alpha 0.47117 0.07678 6.137 8.92e-10 ***
## a 2.05466 0.31852 6.451 1.19e-10 ***
## b 1.45558 0.30703 4.741 2.17e-06 ***
## c 30.27754 1.93150 15.676 < 2e-16 ***
## d 1.25297 0.24567 5.100 3.49e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6598 on 6508 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (917 observations deleted due to missingness)
## Warning: Removed 454 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 9054 3797.3
## 2 9053 3739.5 1 57.813 139.96 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 44842.09
## 2 2 44705.11
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.66023 0.22625 7.338 2.35e-13 ***
## alpha 0.70251 0.05668 12.395 < 2e-16 ***
## a 0.78181 0.40500 1.930 0.0536 .
## b 3.64805 0.40329 9.046 < 2e-16 ***
## c 18.56009 0.45842 40.487 < 2e-16 ***
## d 1.99852 0.17717 11.280 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6427 on 9053 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (208 observations deleted due to missingness)
## Warning: Removed 115 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 9259 5381.4
## 2 9258 5279.2 1 102.13 179.11 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 46596.17
## 2 2 46420.66
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 2.21576 0.30934 7.163 8.51e-13 ***
## alpha 0.67027 0.04732 14.165 < 2e-16 ***
## a 2.14561 0.12609 17.016 < 2e-16 ***
## b 1.79345 0.11498 15.598 < 2e-16 ***
## c 16.78133 0.59405 28.249 < 2e-16 ***
## d 1.08028 0.07988 13.524 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7551 on 9258 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (242 observations deleted due to missingness)
## Warning: Removed 122 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1042 611.60
## 2 1041 599.54 1 12.069 20.956 5.265e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 5298.024
## 2 2 5279.156
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.3150 0.9674 1.359 0.1744
## alpha 0.7081 0.1446 4.897 1.13e-06 ***
## a 1.3185 1.5881 0.830 0.4066
## b 2.6224 1.6247 1.614 0.1068
## c 23.8752 2.9088 8.208 6.60e-16 ***
## d 1.7062 0.8197 2.081 0.0376 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7589 on 1041 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (48 observations deleted due to missingness)
## Warning: Removed 26 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1461 562.19
## 2 1460 558.07 1 4.119 10.776 0.001053 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 5678.475
## 2 2 5669.694
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.6718 0.5104 1.316 0.188317
## alpha 0.4223 0.1238 3.412 0.000663 ***
## a 0.0000 10.9656 0.000 1.000000
## b 2.6048 10.9674 0.238 0.812299
## c 23.9322 8.5379 2.803 0.005129 **
## d 4.1766 10.1509 0.411 0.680798
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6183 on 1460 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (424 observations deleted due to missingness)
## Warning: Removed 200 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 594 658.24
## 2 593 642.29 1 15.944 14.72 0.0001381 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 2860.289
## 2 2 2847.601
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 0.6581 1.1908 0.553 0.58072
## alpha 0.7760 0.1828 4.244 2.54e-05 ***
## a 0.4340 0.9627 0.451 0.65224
## b 3.0156 1.1074 2.723 0.00666 **
## c 20.1594 1.8401 10.955 < 2e-16 ***
## d 1.3486 0.4194 3.215 0.00137 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.041 on 593 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (39 observations deleted due to missingness)
## Warning: Removed 17 rows containing missing values (`geom_point()`).
## [1] "cannot plot residuals"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 4816 1171.2
## 2 4815 1164.7 1 6.5683 27.155 1.956e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 17976.22
## 2 2 17951.11
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.40024 0.30134 4.647 3.46e-06 ***
## alpha 0.42865 0.07987 5.367 8.40e-08 ***
## a 2.28094 0.14232 16.026 < 2e-16 ***
## b 0.60899 0.08256 7.376 1.91e-13 ***
## c 30.49218 1.98928 15.328 < 2e-16 ***
## d 0.82574 0.15904 5.192 2.16e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4918 on 4815 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (17 observations deleted due to missingness)
## Warning: Removed 11 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7147 3539.6
## 2 7146 3503.8 1 35.789 72.993 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 33643.11
## 2 2 33572.43
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.06286 0.25268 4.206 2.63e-05 ***
## alpha 0.77819 0.08733 8.911 < 2e-16 ***
## a 2.32857 0.27855 8.360 < 2e-16 ***
## b 1.46884 0.23819 6.167 7.35e-10 ***
## c 27.60317 1.99164 13.860 < 2e-16 ***
## d 1.18770 0.22998 5.164 2.48e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7002 on 7146 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (49 observations deleted due to missingness)
## Warning: Removed 25 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 745 434.35
## 2 744 430.81 1 3.5355 6.1057 0.0137 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3139.42
## 2 2 3135.29
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 3.26781 1.84192 1.774 0.076451 .
## alpha 0.67407 0.25821 2.611 0.009221 **
## a 1.47179 0.34957 4.210 2.86e-05 ***
## b 1.05698 0.40303 2.623 0.008906 **
## c 38.69332 2.29566 16.855 < 2e-16 ***
## d 0.25262 0.07175 3.521 0.000457 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.761 on 744 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (5 observations deleted due to missingness)
## Warning: Removed 2 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 828 428.21
## 2 827 424.53 1 3.6794 7.1676 0.00757 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3518.799
## 2 2 3513.610
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 4.40938 2.45305 1.798 0.072620 .
## alpha 0.72488 0.25928 2.796 0.005298 **
## a 1.37715 0.37605 3.662 0.000266 ***
## b 0.90911 0.32986 2.756 0.005980 **
## c 26.09391 2.05779 12.681 < 2e-16 ***
## d 0.35507 0.09332 3.805 0.000152 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7165 on 827 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (7 observations deleted due to missingness)
## Warning: Removed 2 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3092 2835.8
## 2 3091 2741.6 1 94.182 106.19 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 16937.51
## 2 2 16834.90
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -1.64465 0.29716 -5.535 3.38e-08 ***
## alpha 0.99393 0.08794 11.302 < 2e-16 ***
## a 6.14292 0.58908 10.428 < 2e-16 ***
## b 4.58403 0.90943 5.041 4.91e-07 ***
## c 34.94264 1.72143 20.299 < 2e-16 ***
## d 0.31656 0.06078 5.208 2.03e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9418 on 3091 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (75 observations deleted due to missingness)
## Warning: Removed 42 rows containing missing values (`geom_point()`).
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1590 1542.8
## 2 1589 1523.8 1 19.044 19.859 8.921e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 8275.762
## 2 2 8257.951
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -2.5413 0.2376 -10.698 < 2e-16 ***
## alpha 0.6625 0.1395 4.748 2.24e-06 ***
## a 0.0000 1.8821 0.000 1
## b 8.0988 2.0030 4.043 5.52e-05 ***
## c 56.8554 6.3381 8.970 < 2e-16 ***
## d 2.4290 0.4874 4.984 6.91e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9793 on 1589 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (284 observations deleted due to missingness)
## Warning: Removed 151 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 333 169.21
## 2 332 163.63 1 5.5875 11.337 0.0008489 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 955.5906
## 2 2 946.2412
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -2.5474 0.3050 -8.353 1.84e-15 ***
## alpha 0.5795 0.1606 3.608 0.000356 ***
## a 0.0000 5.3207 0.000 1.000000
## b 3.4586 5.3738 0.644 0.520276
## c 61.8314 18.5603 3.331 0.000962 ***
## d 2.0674 2.3333 0.886 0.376248
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.702 on 332 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (2 observations deleted due to missingness)
## Analysis of Variance Table
##
## Model 1: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1684 1572.6
## 2 1683 1517.5 1 55.033 61.033 9.807e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 5100.938
## 2 2 5042.772
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau -0.92798 0.59404 -1.562 0.118440
## alpha 0.60538 0.06795 8.909 < 2e-16 ***
## a 0.06516 0.69480 0.094 0.925295
## b 1.92757 0.73647 2.617 0.008942 **
## c 49.63328 3.62429 13.695 < 2e-16 ***
## d 1.98777 0.55580 3.576 0.000358 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9496 on 1683 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (29 observations deleted due to missingness)
## Warning: Removed 12 rows containing missing values (`geom_point()`).
## [1] "cannot plot data with prediction"
## [1] "cannot plot data with prediction"
## model AIC
## 1 1 739.3605
## 2 2 734.0836
##
## Formula: G_MassBal_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * tau/100) * (1 -
## alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## tau 1.1798 2.5654 0.460 0.64601
## alpha 0.7234 0.2525 2.865 0.00455 **
## a 0.0000 0.7983 0.000 1.00000
## b 1.0855 0.8564 1.268 0.20621
## c 84.8244 16.8490 5.034 9.54e-07 ***
## d 1.4393 1.1099 1.297 0.19599
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9014 on 235 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (75 observations deleted due to missingness)
## Warning: Removed 36 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_segment()`).
## Warning: Removed 1 rows containing missing values (`geom_segment()`).
## [1] "cannot plot data with prediction"
| Code | Ecoregion | Sel.Mod |
|---|---|---|
| 211 | Northeastern Mixed Forest | 2 |
| 212 | Laurentian Mixed Forest | 2 |
| 221 | Eastern Broadleaf Forest | 2 |
| 222 | Midwest Broadleaf Forest | 2 |
| 223 | Central Interior Broadleaf Forest | 2 |
| 231 | Southeastern Mixed Forest | 2 |
| 232 | Outer Coastal Plain Mixed Forest | 2 |
| 234 | Lower Mississippi Riverine Forest | 2 |
| 242 | Pacific Lowland Mixed Forest | NA |
| 251 | Prairie Parkland (Temperate) | 2 |
| 255 | Prairie Parkland (Subtropical) | 2 |
| 261 | California Coastal Chaparral Forest and Shrub | NA |
| 262 | California Dry Steppe | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA |
| 313 | Colorado Plateau Semi-Desert | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA |
| 321 | Chihuahuan Semi-Desert | NA |
| 322 | American Semidesert and Desert | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA |
| 332 | Great Plains Steppe | NA |
| 341 | Intermountain Semi-Desert and Desert | NA |
| 342 | Intermountain Semi-Desert | NA |
| 411 | Everglades | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 2 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 2 |
| M223 | Ozark Broadleaf Forest Meadow | 2 |
| M231 | Ouachita Mixed Forest | 2 |
| M242 | Cascade Mixed Forest | 2 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | 2 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | 2 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | 2 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | NA |
| M334 | Black Hills Coniferous Forest | 2 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA |
| Code | Ecoregion | region | n.obs | n.plots | tau | tau.variance | tau.2.5 | tau.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | a | a.2.5 | a.97.5 | b | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 4838 | 2419 | 0.5515401 | 0.0598257 | 0.0720238 | 1.0310563 | 0.6938024 | 0.0067087 | 0.5332269 | 0.8543779 | 0.0000000 | -3.7200270 | 3.7200270 | 3.2997501 | -0.3995932 | 6.999093 | 32.96538 | 29.187819 | 36.74294 | 2.4873010 | 0.7463258 | 4.2282762 |
| 212 | Laurentian Mixed Forest | east | 12962 | 6481 | 1.1876148 | 0.0388168 | 0.8014307 | 1.5737990 | 0.6832251 | 0.0018405 | 0.5991330 | 0.7673172 | 0.5002676 | 0.1243505 | 0.8761848 | 1.8381506 | 1.4561975 | 2.220104 | 25.30091 | 23.777144 | 26.82467 | 2.0439510 | 1.7089602 | 2.3789417 |
| 221 | Eastern Broadleaf Forest | east | 5446 | 2723 | -0.4921082 | 0.0277038 | -0.8184022 | -0.1658141 | 0.7078374 | 0.0052819 | 0.5653631 | 0.8503117 | 0.0000000 | -3.3789373 | 3.3789373 | 4.4367692 | 1.0544933 | 7.819045 | 39.60558 | 34.819439 | 44.39172 | 2.5636857 | 1.2696859 | 3.8576854 |
| 222 | Midwest Broadleaf Forest | east | 3552 | 1776 | 0.0283094 | 0.0690062 | -0.4867282 | 0.5433471 | 0.7115958 | 0.0048089 | 0.5756342 | 0.8475575 | 1.4603509 | 0.9075423 | 2.0131595 | 1.9158937 | 1.3570908 | 2.474697 | 49.13281 | 43.037470 | 55.22816 | 1.6418451 | 1.1510428 | 2.1326474 |
| 223 | Central Interior Broadleaf Forest | east | 6388 | 3194 | -0.0825059 | 0.0337210 | -0.4424867 | 0.2774749 | 0.4711714 | 0.0058952 | 0.3206570 | 0.6216858 | 2.0546598 | 1.4302502 | 2.6790695 | 1.4555816 | 0.8537029 | 2.057460 | 30.27754 | 26.491161 | 34.06392 | 1.2529688 | 0.7713709 | 1.7345668 |
| 231 | Southeastern Mixed Forest | east | 7790 | 3895 | 1.6602295 | 0.0511891 | 1.2167283 | 2.1037306 | 0.7025126 | 0.0032122 | 0.5914139 | 0.8136113 | 0.7818095 | -0.0120881 | 1.5757072 | 3.6480498 | 2.8575020 | 4.438598 | 18.56009 | 17.661479 | 19.45871 | 1.9985204 | 1.6512194 | 2.3458214 |
| 232 | Outer Coastal Plain Mixed Forest | east | 7940 | 3970 | 2.2157636 | 0.0956924 | 1.6093853 | 2.8221419 | 0.6702732 | 0.0022390 | 0.5775188 | 0.7630276 | 2.1456073 | 1.8984365 | 2.3927782 | 1.7934510 | 1.5680713 | 2.018831 | 16.78133 | 15.616858 | 17.94581 | 1.0802794 | 0.9237045 | 1.2368542 |
| 234 | Lower Mississippi Riverine Forest | east | 830 | 415 | 1.3149574 | 0.9358533 | -0.5833092 | 3.2132239 | 0.7080513 | 0.0209036 | 0.4243483 | 0.9917543 | 1.3184695 | -1.7978464 | 4.4347854 | 2.6224194 | -0.5655835 | 5.810422 | 23.87516 | 18.167400 | 29.58293 | 1.7061821 | 0.0977380 | 3.3146262 |
| 242 | Pacific Lowland Mixed Forest | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 1392 | 696 | 0.6718225 | 0.2605392 | -0.3294327 | 1.6730777 | 0.4222983 | 0.0153194 | 0.1795090 | 0.6650876 | 0.0000000 | -21.5100523 | 21.5100523 | 2.6048063 | -18.9087722 | 24.118385 | 23.93220 | 7.184283 | 40.68012 | 4.1766358 | -15.7351727 | 24.0884444 |
| 255 | Prairie Parkland (Subtropical) | east | 444 | 222 | 0.6581040 | 1.4181111 | -1.6806823 | 2.9968902 | 0.7759632 | 0.0334229 | 0.4169113 | 1.1350151 | 0.4340458 | -1.4565741 | 2.3246656 | 3.0155967 | 0.8407385 | 5.190455 | 20.15935 | 16.545353 | 23.77335 | 1.3486419 | 0.5248783 | 2.1724055 |
| 261 | California Coastal Chaparral Forest and Shrub | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | west | 118 | 59 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | west | 154 | 77 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 341 | Intermountain Semi-Desert and Desert | west | 4 | 2 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | west | 2 | 1 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 66 | 33 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 5108 | 2554 | 1.4002378 | 0.0908084 | 0.8094653 | 1.9910102 | 0.4286478 | 0.0063798 | 0.2720584 | 0.5852372 | 2.2809388 | 2.0019204 | 2.5599572 | 0.6089923 | 0.4471307 | 0.770854 | 30.49218 | 26.592285 | 34.39207 | 0.8257441 | 0.5139626 | 1.1375257 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 5186 | 2593 | 1.0628617 | 0.0638472 | 0.5675339 | 1.5581895 | 0.7781929 | 0.0076257 | 0.6070096 | 0.9493762 | 2.3285740 | 1.7825423 | 2.8746056 | 1.4688405 | 1.0019195 | 1.935762 | 27.60317 | 23.698964 | 31.50738 | 1.1877006 | 0.7368730 | 1.6385281 |
| M223 | Ozark Broadleaf Forest Meadow | east | 602 | 301 | 3.2678069 | 3.3926776 | -0.3481769 | 6.8837906 | 0.6740728 | NA | 0.1671705 | 1.1809751 | 1.4717897 | 0.7855302 | 2.1580491 | 1.0569808 | 0.2657631 | 1.848198 | 38.69332 | 34.186590 | 43.20006 | 0.2526235 | 0.1117624 | 0.3934845 |
| M231 | Ouachita Mixed Forest | east | 680 | 340 | 4.4093816 | 6.0174665 | -0.4055597 | 9.2243229 | 0.7248842 | NA | 0.2159590 | 1.2338095 | 1.3771528 | 0.6390356 | 2.1152700 | 0.9091071 | 0.2616430 | 1.556571 | 26.09391 | 22.054798 | 30.13302 | 0.3550674 | 0.1718922 | 0.5382426 |
| M242 | Cascade Mixed Forest | west | 34 | 17 | -1.6446455 | 0.0883049 | -2.2272992 | -1.0619918 | 0.9939271 | 0.0077335 | 0.8214992 | 1.1663550 | 6.1429172 | 4.9878885 | 7.2979458 | 4.5840263 | 2.8008839 | 6.367169 | 34.94264 | 31.567382 | 38.31790 | 0.3165643 | 0.1973925 | 0.4357361 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | west | 330 | 165 | -2.5412962 | 0.0564305 | -3.0072428 | -2.0753496 | 0.6625148 | 0.0194689 | 0.3888307 | 0.9361990 | 0.0000000 | -3.6915653 | 3.6915653 | 8.0988192 | 4.1700612 | 12.027577 | 56.85542 | 44.423410 | 69.28743 | 2.4290362 | 1.4730733 | 3.3849991 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | west | 8 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | west | 0 | 0 | -2.5473810 | 0.0930135 | -3.1473200 | -1.9474420 | 0.5794630 | 0.0257880 | 0.2635677 | 0.8953584 | 0.0000000 | -10.4665460 | 10.4665460 | 3.4586229 | -7.1124288 | 14.029675 | 61.83144 | 25.320750 | 98.34214 | 2.0673628 | -2.5225764 | 6.6573021 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | west | 0 | 0 | -0.9279839 | 0.3528855 | -2.0931221 | 0.2371543 | 0.6053802 | 0.0046175 | 0.4721003 | 0.7386601 | 0.0651589 | -1.2976134 | 1.4279313 | 1.9275747 | 0.4830820 | 3.372067 | 49.63328 | 42.524697 | 56.74187 | 1.9877692 | 0.8976330 | 3.0779055 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | west | 20 | 10 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | west | 22 | 11 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M334 | Black Hills Coniferous Forest | west | 306 | 153 | 1.1798413 | 6.5812153 | -3.8742553 | 6.2339379 | 0.7234150 | 0.0637650 | 0.2259281 | 1.2209019 | 0.0000000 | -1.5726990 | 1.5726990 | 1.0854718 | -0.6016339 | 2.772578 | 84.82438 | 51.629969 | 118.01878 | 1.4392864 | -0.7474002 | 3.6259729 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | west | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
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## Warning: Removed 17 rows containing missing values (`geom_point()`).
## Warning: Removed 17 rows containing missing values (`geom_point()`).
## Warning: Removed 1 rows containing missing values (`geom_hline()`).
## Warning: Removed 18 rows containing missing values (`geom_point()`).
## Warning: Removed 17 rows containing missing values (`geom_point()`).